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Registro Completo |
Biblioteca(s): |
Embrapa Territorial. |
Data corrente: |
22/04/2008 |
Data da última atualização: |
22/08/2014 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
LU, D.; BATISTELLA, M.; MORAN, E. |
Afiliação: |
D. Lu ( Indiana University); Batistella, M. (Embrapa Monitoramento por Satélite); E. Moran ( Indiana University Bloomington Indiana USA). |
Título: |
Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM + and Radarsat data. |
Ano de publicação: |
2007 |
Fonte/Imprenta: |
International Journal of Remote Sensing, v. 28, n. 24, p. 5447-5459, 2007. |
ISBN: |
1366-5901 |
DOI: |
16.1080f01431160701227596 |
Idioma: |
Inglês |
Conteúdo: |
Land-cover classification with remotely sensed data in moist tropical regions in a challenge due to the complex biophysical conditions. This paper explores techniques to improve land-cover classification accuracy through a comparative analysis of different combinations of spectral signatures and textures from Landsat Enhanced Thematic Mapper Plus (ETM +) and Radarsat data. A wavelet-merging technique was used to integrate Landsat ETM + multispectral and panchromatic data or Radarsat data. Grey-level co-occurrence matrix (GLCM) textures based on Landsat ETM + panchromatic of Radarsat data and different sizes of moving windows were examined. A maximum-likelihood classifier was used to implement image classification for different combinations. This research indicates the important role of textures in improving land-cover classification accuracies in Amazonian environments. ... |
Palavras-Chave: |
Amazon; land-cover; Landsat ETM+. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/107127/1/2101.pdf
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Marc: |
LEADER 01492naa a2200205 a 4500 001 1017678 005 2014-08-22 008 2007 bl uuuu u00u1 u #d 022 $a1366-5901 024 7 $a16.1080f01431160701227596$2DOI 100 1 $aLU, D. 245 $aLand-cover classification in the Brazilian Amazon with the integration of Landsat ETM + and Radarsat data. 260 $c2007 520 $aLand-cover classification with remotely sensed data in moist tropical regions in a challenge due to the complex biophysical conditions. This paper explores techniques to improve land-cover classification accuracy through a comparative analysis of different combinations of spectral signatures and textures from Landsat Enhanced Thematic Mapper Plus (ETM +) and Radarsat data. A wavelet-merging technique was used to integrate Landsat ETM + multispectral and panchromatic data or Radarsat data. Grey-level co-occurrence matrix (GLCM) textures based on Landsat ETM + panchromatic of Radarsat data and different sizes of moving windows were examined. A maximum-likelihood classifier was used to implement image classification for different combinations. This research indicates the important role of textures in improving land-cover classification accuracies in Amazonian environments. ... 653 $aAmazon 653 $aland-cover 653 $aLandsat ETM+ 700 1 $aBATISTELLA, M. 700 1 $aMORAN, E. 773 $tInternational Journal of Remote Sensing$gv. 28, n. 24, p. 5447-5459, 2007.
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Embrapa Territorial (CNPM) |
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